# How to calculate median, 25th, and 75th percentile values in a Pandas Series?

I was learning and exploring some `series` statistics that are normally used in the analysis of the data and found out about the median value, the 25th percentile value, and the 75th percentile value. Can someone provide me with alternative ways of finding these statistical values? I have attached the way I found and used below:

#### The 25th and 75th Percentile Values:

Also, I would appreciate it if someone also tells me more about what is meant by a `percentile` and what `25th` and `75th` percentile values are.

• The `quantile()` method returns the value at the given quantile of the series. To find the median value, we can use `q=0.5`.

• In statistics, a quantile is a value that divides a data distribution into intervals of equal probability, and they are useful for summarizing the distribution of a dataset.

• Specifying `q = 0.5` means the value that divides the data into two equal parts; hence, this is how we get the median value.

@mubashir_rizvi, `Percentile` is defined as the value below which a given percentage of observations in a group of data falls.
`25th percentile` is also known as the first quartile, and it is a statistical measure that indicates the value below which 25% of the data lies.
`75th percentile` is also known as the third quartile, and it is a statistical measure that indicates the value below which 75% of the data lies.

To find the 25th and 75th percentiles, you can call the `scoreatpercentile()` function with a parameter of 25 and 75. The `scipy.stats.scoreatpercentile()` function can be used to find the `nth` percentile of a series. You can also pass a list of percentile values we want. Let’s see the example given below for a better understanding: